Data Architect Intermediate

University Of Michigan (The Regents @ Ann Arbor)•Ann Arbor, MI

42d•Hybrid

About The Position

Health Information Technology & Services (HITS) plays a role in the success of Michigan Medicine by providing clinicians, educators, researchers, students, and staff with technology-related information, products, and support. HITS also provides institutional expertise related to IT strategy, security, infrastructure, and resource management. Health Information Technology and Services (HITS) at the U-M Michigan Medicine has an exciting opportunity for a Data Architect Intermediate on its Enterprise Data and Information Services (EDIS), Data Integration and Architecture Team. EDIS is responsible for supporting and building Michigan Medicine's Enterprise Data Warehouse environment and application integration activities. Michigan Medicine's Enterprise Data Warehouse serves as a vital conduit of information to leaders across the institution. A candidate for this position should possess experience in database design and development. That experience should include extracting, transforming, and loading (ETL) data between systems. The preferred candidate will have experience integrating data using a variety of approaches, that may include flat-file extracts, Enterprise Service Buses (ESB), ODBC APIs, Restful APIs, Cloud services.

Requirements

Bachelor's degree in a related field and/or equivalent combination of education, certification and experience.
2-3 years of IT related experience.
Experience working closely with, or as a member of, enterprise data warehousing teams.
Excellent analytical and creative problem-solving skills.
Solid and effective written, interpersonal, and verbal communication skills.
Strong organizational skills with attention to detail.
Able to work on multiple priorities in a deadline-driven environment.
Strong SQL programming language skills.

Nice To Haves

2 or more years of demonstrated experience in a related role requiring confidentiality, timeliness, customer service, organization, prioritization, troubleshooting, and working independently.
2 or more years of experience with the full software lifecycle of system implementation including requirements analysis, design, implementation, quality assurance testing and documentation.
Experience building new data models while ensuring consistency and integration with mature warehouse structure.
Experience building data integration solutions that leverage restful APIs or message-based technology.
Experience with scripting and/or object-oriented programming languages.
Experience using ETL development platforms like Informatica or MS SSIS.
Experience working with Azure SaaS or PaaS Cloud service offerings.
Experience in one or more disciplines such as Health Care, Financial, Human Resources, Student Administration, and Sponsored Research.
Familiarity with Enterprise Resource Planning (ERP) and Enterprise Medical Record (EMR) solutions.
Ability to work effectively with management, team members, and colleagues from other departments and projects.
Experience developing on Oracle and SQL Database platforms.
Knowledge of data warehouse design concepts.
Knowledge of systems development methodologies including waterfall and agile approaches.
Demonstrated skills in data analysis and process modeling tools and techniques.

Responsibilities

Gather requirements for the design and development of data structures and data extracts to support comprehensive data collection, loading, and extraction for complex analyses.
Model information in a way that customers can easily consume it.
Work with business analysts to develop key measures that drive University metrics.
Work with data experts to ensure that data is stored accurately.
Write SQL queries that validate the data is accurate and meets business requirements.
Design, build, and support ETL applications that meet our customer's data needs.
Research and share discoveries about new technologies, frameworks, and architectural approaches to data integration and warehousing.
Actively monitor and respond to production support issues.
Proactively recommend application and architecture modifications that will improve the reliability, relevance, timeliness, completeness, and accuracy of the data we support.
Collaborate effectively with a team of business analysts, data architects, ETL developers, and DBAs on best practices for all of our solutions.